ArticleScientific data2026
A high-resolution dataset on costs and greenhouse gas emissions of battery recycling in China.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- A high-resolution dataset on costs and greenhouse gas emissions of battery recycling in China.Scientific data · 2026Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The rapid growth of electric vehicle deployment is expected to lead to a surge in retired batteries over the coming decades, drawing increasing attention to battery recycling as part of sustainability transitions. However, existing assessments of battery recycling costs and greenhouse gas (GHG) emissions are often conducted at coarse spatiotemporal scales, limiting their ability to capture regional heterogeneity and long-term dynamics. Here, we present a high-resolution dataset of costs and GHG emissions for hydrometallurgical recycling processes in China, covering 337 prefecture-level cities from 2020 to 2060 and disaggregated across six typical battery cathode chemistries. The dataset is constructed using a process-based framework that integrates spatial and temporal heterogeneities in battery retirements, factor costs, and energy mixes. By providing a consistent and structured representation of recycling impacts, this dataset enables comparative analyses across regions and time horizons and supports further research on secondary material impact assessment and recycling network design.
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Registered trials
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